CASE STUDY
Bank Reconciliation Automation for a Multi-Entity Retail Organization
An automated settlement matching and reconciliation pipeline connecting Azure SQL Managed Instance with Microsoft Dynamics 365 Business Central across 20 retail store bank accounts.
Cognic RetailRec
Search retail store settlements…
Multi-Store POS & Bank Settlement Matching
20
Store Entities
$2.4M
Daily Settled Volume
99.1%
Matched Settlement
8
Open Discrepancies
| Store / Entity | POS Batch ID | Settlement Date | Deposit Amount | Status | Confidence |
|---|---|---|---|---|---|
| Store #104 – Chicago | POS-8921-A | 10/24/2023 | $42,580.20 | Matched to Bank | 100% |
| Store #108 – Dallas | POS-8922-C | 10/24/2023 | $68,910.50 | Matched to Bank | 99% |
| Store #112 – Miami | POS-8923-B | 10/24/2023 | $31,400.00 | Matched to Bank | 98% |
| Store #115 – Seattle | POS-8924-D | 10/23/2023 | $19,250.75 | Card Fee Variance | 88% |
| Store #120 – New York | POS-8925-A | 10/23/2023 | $115,800.00 | Matched to Bank | 100% |
20 Store Entities Multi-Location Scope
Daily automated reconciliation across 20 distinct legal entities
4 Hours → 15 Mins Daily Processing Time
93% reduction in daily manual spreadsheet reconciliation time
$2.4M Daily Transaction Flow
High-volume matching of store POS registers against bank deposits
99.1% Automated Accuracy
Precise fee netting, interchange fees, and multi-tender matching
What is multi-entity retail reconciliation?
Multi-entity retail reconciliation automates the aggregation and matching of point-of-sale (POS) terminal settlements, e-commerce payment gateways, and merchant deposits against bank statements and Microsoft Dynamics 365 Business Central ledgers across numerous legal entities.
A Smarter Way to Reconcile Retail Networks
The Challenge
Finance teams manually stitching together fragmented Excel files for 20 store locations with mismatched settlement dates and merchant fees.
The Solution
Cloud data pipeline in Azure SQL Managed Instance pairing gross sales, merchant deductions, and bank receipts with automated ERP posting.
The Outcome
Daily close completed before opening bell, total elimination of deposit discrepancies, and unified multi-store cash visibility.
The Challenge
Multi-store retail chains face complex settlement challenges where daily register totals rarely match lump-sum bank deposits due to delayed batch processing and processing fees.
20 distinct store entities with independent bank accounts
Batch settlements timing lag (T+1 to T+3 business days)
Interchange fee and merchant processor deductions unbundled
Multi-tender transactions (Credit, Debit, Gift Card, Cash)
Heavy reliance on fragile multi-tab Excel workbooks
Delayed identification of store-level cash register shortages
Labor-intensive manual journal creation in Business Central
Lack of centralized management reporting across retail network
Traditional Retail Reconciliation vs. Cognic Automated Engine
| Workflow Stage | Traditional Manual Workflow | Cognic AI-Powered Engine |
|---|---|---|
| Data Ingestion | Store managers email daily closing sheets; accounting downloads 20 bank portals | Automated daily ingestion from POS systems, merchant gateways, and bank SFTP feeds |
| Settlement Splitting | Manual calculation of interchange fees, discount rates, and net deposits in Excel | Automated fee netting and multi-tender breakdown logic in Azure SQL |
| Entity Isolation | 20 separate spreadsheet files handled sequentially by multiple bookkeepers | Unified multi-tenant data architecture maintaining clean entity isolation and roll-ups |
| Exception Handling | Discrepancies investigated weeks later during stressful month-end close | Same-day discrepancy alerts with direct drill-down to register transaction numbers |
| ERP Synchronization | Manual entry of bank deposit journals in Dynamics 365 Business Central | Automated posting of reconciled general journal batches via Business Central APIs |
| Executive Visibility | Weekly or monthly delayed reporting on overall network cash flow | Real-time Power BI dashboard showing daily cash settlement status per store |
The Multi-Entity Retail Reconciliation Engine
Three core pillars delivering automated reconciliation for distributed retail networks.
01
POS & Gateway Ingestion Pipeline
Connects all retail store POS terminals, merchant gateways, and bank feeds.
• Daily POS batch parsing
• Merchant fee calculation engine
• Multi-bank statement normalization
→
02
Azure SQL Matching & Rules Engine
Executes high-speed reconciliation rules across tens of thousands of daily lines.
• Date window tolerance rules
• Multi-tender split allocation
• Shortage & overage detection
→
03
Dynamics 365 ERP Posting & Reporting
Synchronizes reconciled journals and streams analytics to finance controllers.
• Automated BC journal creation
• Store variance reporting
• Executive Power BI dashboards
→
Store Audits
Instant visibility into register discrepancies
ERP Sync
Direct general journal posting into D365
Executive BI
Consolidated network-wide cash reporting
Multi-Entity Data Pipeline Architecture
Scalable cloud infrastructure connecting retail registers to ERP ledgers.
1 POS & Bank Ingestion
› 20 Store POS Feeds
› Merchant Processors
› Bank Statement Files
› Automated SFTP
› Azure Blob Intake
2 Data Transformation
› Azure SQL Managed Instance
› Tender Decomposition
› Merchant Fee Netting
› Date Lag Normalization
› Entity Mapping
3 Matching Engine
› Multi-Variable Matcher
› Tolerance Thresholds
› Variance Isolation
› Anomaly Flagging
› Audit Logging
4 ERP & Analytics
› Dynamics 365 BC API
› Posted Cash Journals
› Store Performance Alerts
› Power BI Dashboards
› Executive Reports
Traceable Audit Flow: From POS Register to Consolidated Ledger
Every dollar tracked with verifiable lineage from customer swipe to audited financial statement.
Register POS
→
Merchant Batch
→
Bank Deposit
→
Azure SQL Rules
→
Store Exception
→
D365 Ledger
Data & Automation Layer
High-throughput data engineering powering real-time retail reconciliation.
Azure SQL High-Volume Engine
Executes complex reconciliation queries in milliseconds
Tender Decomposition Logic
Separates Visa, MC, Amex, Discover, and cash drawer balances
Automatic Fee Deductions
Reconciles net deposits against contractual merchant fee schedules
Confidence Scoring Engine
Validates exact store entity matching and journal alignment
Automated Exception Alerting
Immediate Slack/Teams notifications for overage/shortage events
Retail Controller Workbench
Centralized command center for managing store-level discrepancies.
| Store Entity | POS Batch | Date | Amount | Flag | Confidence | Action |
|---|---|---|---|---|---|---|
| Store #104 – Chicago | POS-8921-A | 10/24/2023 | $42,580.20 | Matched to Bank | 100% | |
| Store #108 – Dallas | POS-8922-C | 10/24/2023 | $68,910.50 | Matched to Bank | 99% | |
| Store #112 – Miami | POS-8923-B | 10/24/2023 | $31,400.00 | Matched to Bank | 98% | |
| Store #115 – Seattle | POS-8924-D | 10/23/2023 | $19,250.75 | Card Fee Variance | 88% |
Enterprise Retail Data Security
Robust cloud architecture meeting strict PCI-DSS and financial security standards.
Azure SQL MI
PCI-DSS Compliant
End-to-End Encryption
Multi-Entity RBAC
Secure SFTP Feeds
Immutable Logs
Technology Stack
Key technologies powering the production deployment.
Azure SQL MI
Dynamics 365 BC
Power BI
C# .NET
Azure Data Factory
REST APIs
SQL Stored Procedures
Docker
Azure Key Vault
SSIS Pipelines
What Changed
Key operational and efficiency improvements.
Reconciliation cycle reduced from 4 hours daily to under 15 minutes
Unified daily settlement across 20 retail store locations
Automated deduction calculation for credit card interchange fees
Real-time discrepancy detection for cash register overages/shortages
Seamless multi-entity general journal posting into Business Central
Built for Retail Executives
Empowering retail finance leaders with automated multi-store visibility.
VP of Retail Finance
Consolidated cash positioning and real-time store performance tracking.
Retail Controllers
Ensure accurate ledger postings and eliminate month-end reconciliation chaos.
Store Operations Directors
Immediate visibility into register discrepancies and bank deposit confirmations.